Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-26T16:36:14.520Z Has data issue: false hasContentIssue false
  • English
  • Français

Patient and clinician experiences of a computerised cognitive battery for use after concussion: a preliminary qualitative study

Published online by Cambridge University Press:  12 October 2020

C. Macleod ,
L. J. Surgenor ,
W. Levack ,
J. Hackney ,
A. Theadom ,
R. J. Siegert ,
N. D. Silverberg  and
D. L. Snell
C. Macleod
Affiliation:
Department of Orthopaedic Surgery & Musculoskeletal Medicine, University of Otago, Christchurch, New Zealand
L. J. Surgenor
Affiliation:
Department of Psychological Medicine, University of Otago, Christchurch, New Zealand
W. Levack
Affiliation:
Rehabilitation Teaching and Research Unit, University of Otago, Wellington, New Zealand
J. Hackney
Affiliation:
Burwood Concussion Clinic, Christchurch, New Zealand
A. Theadom
Affiliation:
Department of Psychology and Rehabilitation, AUT University, Auckland, New Zealand
R. J. Siegert
Affiliation:
Department of Psychology and Rehabilitation, AUT University, Auckland, New Zealand
N. D. Silverberg
Affiliation:
Division of Physical Medicine and Rehabilitation, Department of Medicine, University of British Columbia, Vancouver, Canada Rehabilitation Research Program, GF Strong Rehab Centre, Vancouver, Canada
D. L. Snell*
Affiliation:
Department of Orthopaedic Surgery & Musculoskeletal Medicine, University of Otago, Christchurch, New Zealand Burwood Concussion Clinic, Christchurch, New Zealand
*
*Corresponding author. Email: [email protected]
Get access

Abstract

Objective:

The Cognition Battery of the National Institute of Health (NIH) Toolbox for Assessment of Neurological and Behavioural Function is a computerised neuropsychological battery recommended for clinical practice, neurological research and clinical trials. We investigated the utility of the NIH Toolbox Cognition Battery (NIHTB-CB) for people with concussion.

Methods:

In this small qualitative study, semi-structured interviews were conducted with five adults with concussion who were participating in a larger study using the NIHTB-CB. Three clinician participants and two cultural advisors familiar with the tool were also interviewed. Interview transcripts were analysed using a general thematic approach and qualitative description.

Results:

Participants described both positive and negative experiences with the NIHTB-CB and using qualitative description, their experiences were organised into three broad themes: (1) using technology for cognitive testing made sense, (2) there were some cultural relevance questions and (3) cognitive testing after concussion could have challenges. They were positive about the computerised format and range of domains assessed for the concussion context but identified the contextual relevance of some content as having potential to impact on performances.

Conclusion:

This was a small study examining the experiences of a select group of participants, but nevertheless does suggest a need for future research validating the NIHTB-CB for use in different cultural and clinical contexts.

Keywords

NIH Toolbox Cognition Batterymild traumatic brain injurycomputerised cognitive assessment
Type
Articles
Information
Brain Impairment , Volume 22 , Issue 2 , September 2021 , pp. 189 - 204
Copyright
© Australasian Society for the Study of Brain Impairment 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Archibald, M. M., Ambagtsheer, R. C., Casey, M. G., & Lawless, M. (2019). Using Zoom Videoconferencing for qualitative data collection: Perceptions and experiences of researchers and participants. International Journal of Qualitative Methods, 18, 1–8.CrossRefGoogle Scholar
Bannigan, K., & Watson, R. (2009). Reliability and validity in a nutshell. Journal of Clinical Nursing, 18, 3237–3243.CrossRefGoogle Scholar
Bauer, R. M., Iverson, G. L., Cernich, A. N., Binder, L. M., Ruff, R. M., & Naugle, R. I. (2012). Computerized neuropsychological assessment devices: Joint position paper of the American Academy of Clinical Neuropsychology and the National Academy of Neuropsychology. The Clinical Neuropsychologist, 26(2), 177–196.CrossRefGoogle ScholarPubMed
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.CrossRefGoogle Scholar
Carter, N., Bryant-Lukusius, D., DiCenso, A., Blythe, J., & Neville, A. J. (2014). The use of triangulation in qualitative research. Oncology Nursing Forum, 41(5), 545–547.CrossRefGoogle ScholarPubMed
Dudley, M. D., Barker-Collo, S. L., Wilson, D. L., & Garrett, N. K. (2019). Factors associated with Māori performance on the WAIS-IV. Archives of Clinical Neuropsychology, 34(7), 1203–1216.CrossRefGoogle ScholarPubMed
Feigin, V. L., Theadom, A., Barker-Collo, S., Starkey, N. J., McPherson, K., Kahan, M., Dowell, A., Brown, P., Parag, V., Kydd, R., Jones, K., Jones, A., Ameratunga, S., & the BIONIC Study Group. (2013). Incidence of traumatic brain injury in New Zealand: A population-based study. The Lancet Neurology, 12(1), 53–64.CrossRefGoogle ScholarPubMed
Feldstein, S. N., Keller, F. R., Portman, R. E., Durham, R. L., Klebe, K. J., & Davis, H. P. (1999). A comparison of computerized and standard versions of the Wisconsin Card Sorting Test. The Clinical Neuropsychologist, 13(3), 303–313.CrossRefGoogle ScholarPubMed
Gardner, R. C., & Yaffe, K. (2015). Epidemiology of mild traumatic brain injury and neurodegenerative disease. Molecular and Cellular Neuroscience, 66, 75–80.CrossRefGoogle ScholarPubMed
Gershon, R. C., Cella, D., Fox, N. A., Havlik, R. J., Hendrie, H. C., & Wagster, M. V. (2010). Assessment of neurological and behavioural function: The NIH Toolbox. The Lancet Neurology, 9, 138–139.CrossRefGoogle ScholarPubMed
Gershon, R. C., Wagster, M. V., Hendrie, H. C., Fox, N. A., Cook, K. F., & Nowinski, C. J. (2013). NIH Toolbox for assessment of neurological and behavioural function. Neurology, 80(11 Supplement 3), S2–S6.CrossRefGoogle Scholar
Guilmette, T. J., Sweet, J. J., Hebben, N., Koltai, D., Mahone, E. M., Spiegler, B. J., Stucky, K. M., Westerveld, M., & Conference Participants. (2020). American Academy of Clinical Neuropsychology consensus conference statement on uniform labelling of performance test scores. The Clinical Neuropsychologist, 34(3), 437–453.CrossRefGoogle Scholar
Heaton, R. K., Akshoomoff, N., Tulsky, D., Mungas, D., Weintraub, S., Dikmen, S., Beaumont, J., Casaletto, K. B., Conway, K., Slotkin, J., & Gershon, R. (2014). Reliability and validity of composite scores from the NIH Toolbox Cognition Battery in adults. Journal of the International Neuropsychological Society, 20, 588–598.CrossRefGoogle ScholarPubMed
Holdnack, J. A., Iverson, G. L., Silverberg, N. D., Tulsky, D. S., & Heinemann, A. W. (2017). NIH Toolbox cognition tests following traumatic brain injury: Frequency of low scores. Rehabilitation Psychology, 62(4), 474.CrossRefGoogle ScholarPubMed
Iverson, G. L. (2019). Network analysis and precision rehabilitation for the post-concussion syndrome. Frontiers in Neurology, 10, Article 489.CrossRefGoogle Scholar
Iverson, G. L., Brooks, B. L., Ashton, V. L., Johnson, L. G., & Gualtieri, C. T. (2009). Does familiarity with computers affect computerized neuropsychological test performance? Journal of Clinical and Experimental Neuropsychology, 31(5), 594–604.CrossRefGoogle ScholarPubMed
Iverson, G. L., Echemendia, R. J., LaMarre, A. K., Brooks, B. L., & Gaetz, M. B. (2012). Possible lingering effects of multiple past concussions. Rehabilitation Research and Practice, 3: 316575.Google Scholar
Lim, Y. Y., Prang, K. H., Cysique, L., Pietrzak, R. H., Snyder, P. J., & Maruff, P. (2009). A method for cross-cultural adaptation of a verbal memory assessment. Behavior Research Methods, 41(4), 1190–1200.CrossRefGoogle ScholarPubMed
Malda, M., van de Vijver, F., Srinivasan, K., Transler, C., Sukumar, P., & Rao, K. (2008). Adapting a cognitive test for a different culture. Psychology Science Quarterly, 50(4), 415–468.Google Scholar
Mansur, A., Hauer, T. M., Hussain, M. W., Alatwi, M. K., Tarazi, A., Khodadadi, M., & Tator, C. H. (2018). A nonliquid crystal display screen computer for treatment of photosensitivity and computer screen intolerance in post-concussion syndrome. Journal of Neurotrauma, 35(16), 1886–1894.CrossRefGoogle ScholarPubMed
Menon, D., Schwab, K., Wright, D., & Maas, A. (2010). Position statement: Definition of traumatic brain injury. Archives of Physical Medicine and Rehabilitation, 91, 1637–1640.CrossRefGoogle ScholarPubMed
National Institutes of Health and North Western University. (2006–2018). NIH Toolbox for Assessment of Neurological and Behavioral Function: Administrator’s manual, iPad version 1.17 and up. Retrieved from www.nihtoolbox.org.Google Scholar
Parsons, T. D., McMahan, T., & Kane, R. (2018). Practice parameters facilitating adoption of advanced technologies for enhancing neuropsychological assessment paradigms. The Clinical Neuropsychologist, 32(1), 16–41.CrossRefGoogle ScholarPubMed
Porrselvi, A. P., & Shankar, V. (2018). Limitations of integrating technology in cognitive testing of non-verbal memory. International Journal of Indian Psychology, 6(3), 167–173.Google Scholar
Rabin, L. A., Spadaccini, A. T., Brodale, D. L., Grant, K. S., Elbulok-Charcape, M. M., & Barr, W. B. (2014). Utilization rates of computerized tests and test batteries among clinical neuropsychologists in the United States and Canada. Professional Psychology: Research and Practice, 45(5), 368–377.CrossRefGoogle Scholar
Robillard, J. M., Lai, J. A., Wu, J. M., Feng, T. L., & Hayden, S. (2018). Patient perspectives of the experience of a computerized cognitive assessment in a clinical setting. Alzheimer’s and Dementia: Translational Research & Clinical Interventions, 4, 297–303.Google ScholarPubMed
Sandelowski, M. (2000). Whatever happened to qualitative description? Research in Nursing & Health, 23(4), 334–340.3.0.CO;2-G>CrossRefGoogle ScholarPubMed
Scott, E. P., Sorrell, A., & Benitez, B. (2019). Psychometric properties of the NIH Toolbox Cognition Battery in healthy older adults: Reliability, validity, and agreement with standard neuropsychological tests. Journal of the International Neuropsychological Society, 25(8), 857–867.CrossRefGoogle ScholarPubMed
Silverberg, N. D., Crane, P. K., Dams-O’Connor, K., Holdnack, J., Ivins, B. J., Lange, R. T., Manley, G. T., McCrea, M., & Iverson, G. L. (2017). Developing a cognition endpoint for traumatic brain injury clinical trials. Journal of Neurotrauma, 34(2), 363–371.CrossRefGoogle ScholarPubMed
Thomas, D. R. (2006). A general inductive approach for analysing qualitative evaluation data. American Journal of Evaluation, 27(2), 237–246.CrossRefGoogle Scholar
Van de Vijver, F., & Tanzer, N. K. (2004). Bias and equivalence in cross-cultural assessment: An overview. Revue Européenne de Psychologie Appliquée/European Review of Applied Psychology, 54(2), 119–135.CrossRefGoogle Scholar
Wechsler, D. (2008). Wechsler adult intelligence scale (4th ed.). San Antonio, TX: Pearson, Inc.Google Scholar
Weintraub, S., Dikmen, S. S., Heaton, R. K., Tulsky, D. S., Zelazo, P. D., Bauer, P. J., Cariozzi, N. E., Slotkin, D. B., Wallner-Allen, K., Fox, N. A., Beaumont, J. L., Mungars, D., Nowinski, C. J., Richler, J., Deocampo, J. A., Manly, J., Borosh, B., Havlik, R., Conway, K., … Gershon, R. C. (2013). Cognition assessment using the NIH Toolbox. Neurology, 80(11 Supplement 3), S54–S64.CrossRefGoogle ScholarPubMed
Wild, K., Howieson, D., Webbe, F., Seelye, A., & Kaye, J. (2008). Status of computerized cognitive testing in aging: A systematic review. Alzheimer’s & Dementia, 4(6), 428–437.CrossRefGoogle ScholarPubMed
Zoom Video Communications Inc. (2016). Security guide. Zoom Video Communications Inc. Retrieved from https://d24cgw3uvb9a9h.cloudfront.net/static/81625/doc/Zoom-Security-WhitePaper.pdf.Google Scholar